(530d) A Novel Mathematical Model for Short-Term and Medium-Term Scheduling of Multipurpose Batch Plants
In this work, we develop a novel unit-specific event-based formulation for short-term scheduling of multipurpose batch plants, where production and consumption tasks related to the same state are allowed to take place at the same event, which could significantly reduce the number of event points that are required to generate optimal solution. The definition of recycling tasks from Li and Floudas  and recycling states is employed to avoid infeasibility arising from allowing recycling tasks to take place at the same event points with their related consumption tasks with the same recycling states. To further reduce the number of event points that are required, we introduce a new binary variable to explicitly identify the specific production task or storage that provide materials to a consumption task. We sequence a consumption task only with the related specific production task that provides materials to this consumption task, not all related production tasks. Additionally, when a task consumes materials that already exist in storage, we do not need to sequence it with any production task. To illustrate the capability of our proposed model, we solve a number of examples that are well established in the literature. The computational results demonstrate that the proposed model significantly reduces the number of event points that are required and decreases the model size. As a result, our proposed model requires less computational time to generate the optimal solution compared to the existing models. We then incorporate our proposed model into the rolling horizon framework  to solve medium-term scheduling of large-scale industrial batch plants. The comparison results demonstrate that better profit could be generated with our proposed model compared to that of Janak et al. .
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